Cardiac monitoring—particularly ambulatory monitoring—includes long-term monitoring of ECG signals to detect various type of heart rhythm disorders. The amount of ECG data collected, however, precludes (or makes cost-prohibitive) health care professional (HCP) review of the data. Automatic processing of the collected ECG data is utilized to detect and capture ECG segments corresponding with detected heart rhythm disorders. However, while some of the ECG segments captured correspond with an actual heart rhythm disorder (i.e., a true positive event), other ECG segments are incorrectly identified as corresponding to a heart rhythm disorder (i.e., a false positive event). On the other hand, capturing multiple ECG segments corresponding with the same heart rate rhythm disorder is not always diagnostically relevant. For instance, the first tachy150 event captured is diagnostically relevant, but the other tachy150 events captured on the same day may not be. In addition, each captured ECG segment identified as corresponding to a heart rhythm disorder and captured represents a cost. That cost includes the cost of storing the captured ECG segment either on the monitoring device or externally, the cost of power required to communicate the captured ECG segment from the monitoring device to a remote monitoring center, and/or time required for a HCP to review the captured ECG episode and determine whether action is required. Thus, it is beneficial to reduce the ECG segments incorrectly identified as corresponding to a heart rhythm disorder (i.e., minimize false positive events). However, it is also important to ensure that heart rhythm disorders are detected and corresponding ECG segments captured and provided to a human HCP for review (i.e., avoid missing detection of positive events, or false negative).
It would therefore be beneficial to provide a monitoring system that balances these concerns to ensure clinically relevant ECG segments are captured while maintaining a low-cost system.